AIMC Topic: Algorithms

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Artificial intelligence and machine learning applications in biopharmaceutical manufacturing.

Trends in biotechnology
Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biother...

EISA-Score: Element Interactive Surface Area Score for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling
Molecular surface representations have been advertised as a great tool to study protein structure and functions, including protein-ligand binding affinity modeling. However, the conventional surface-area-based methods fail to deliver a competitive pe...

SOLO-SLAM: A Parallel Semantic SLAM Algorithm for Dynamic Scenes.

Sensors (Basel, Switzerland)
Simultaneous localization and mapping (SLAM) is a core technology for mobile robots working in unknown environments. Most existing SLAM techniques can achieve good localization accuracy in static scenes, as they are designed based on the assumption t...

A Domestic Trash Detection Model Based on Improved YOLOX.

Sensors (Basel, Switzerland)
Domestic trash detection is an essential technology toward achieving a smart city. Due to the complexity and variability of urban trash scenarios, the existing trash detection algorithms suffer from low detection rates and high false positives, as we...

A digital mask to safeguard patient privacy.

Nature medicine
The storage of facial images in medical records poses privacy risks due to the sensitive nature of the personal biometric information that can be extracted from such images. To minimize these risks, we developed a new technology, called the digital m...

Pulse Signal Analysis Based on Deep Learning Network.

BioMed research international
Pulse signal is one of the most important physiological features of human body, which is caused by the cyclical contraction and diastole. It has great research value and broad application prospect in the detection of physiological parameters, the dev...

Application of Genetic Algorithm and U-Net in Brain Tumor Segmentation and Classification: A Deep Learning Approach.

Computational intelligence and neuroscience
The development of unusual cells in the cerebrum causes brain cancer. It is classified primarily into two classes: a noncarcinogenic (benign) type of growth and cancerous (malignant) growth. Early detection of this disease is a quintessential task fo...

MalFuzz: Coverage-guided fuzzing on deep learning-based malware classification model.

PloS one
With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep learning models have also received more and more attention. Nowadays, malware has become a huge sec...

Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have ...

Jointly estimating bias field and reconstructing uniform MRI image by deep learning.

Journal of magnetic resonance (San Diego, Calif. : 1997)
Bias field is one of the main artifacts that degrade the quality of magnetic resonance images. It introduces intensity inhomogeneity and affects image analysis such as segmentation. In this work, we proposed a deep learning approach to jointly estima...